At first I was a little annoyed that AngelList makes the salary and equity fields mandatory when you fill out a job. But it looks like a lot of companies take those values semi-seriously, so it might be an interesting dataset to look at.
Fortunately, a screen scraped copy of their jobs postings fell off a truck the other day, so I took a look at it: angellist data.xslx
There are 4630 posted jobs, 80% are full time, but people are also looking for Cofounders (11.4%), Interns (5.0%) and Contractors (3.5%). I’ve manually scrubbed a few jobs out, somewhat arbitrarily (although I MOOV is really offering $10 billion for a Technical Co-Founder).
San Francisco is a quarter of the jobs, New York is next with 11%. In fifth place with 3.8%, London is the larget international destination. Toronto sneaks into 10th with 1.5% of the openings.
So the real question is: Who is better San Francisco or New York?
|New York City||494||$77,256||2.34%|
It’s ambiguous, NY gives more equity on average, SF gives more money.
But to do an apples to apples comparison, I’ll strip out everything except full time positions, remove posts with no location specified and do a bit more clean up (such as remove positions with 0 salary and 0 equity).
Actually, while we’re at it, according to this word frequency counter here are the 5 most common words in job titles:
Let’s also limit ourselves to just jobs with “engineer” or “developer” in the title, there’s still almost 2000 postings.
|New York City||227||11.7%|
Here’s the average salary ( just (min+max)/2 ) and equity broken down by the most popular cities:
|Group||Count||Avg Salary||%||Avg Equity||%|
|New York City||227||$89,905||105%||1.70%||118%|
San Francisco has some competition from Mountain View, but the SF/Palo Alto/MV numbers are all roughly in the same ballpark, the London numbers may be in pounds and the Toronto numbers may be in Celsius, but nothing looks unreasonable.
The salaries are a little less than what you find posted elsewhere which makes sense (even if those ranges are lower than the word on the street). If you look at the raw data you’ll see the ranges are almost sensible too.
In this case, I’m giving the tie to the home team, but here’s the data: